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Validation and sensitivity test of the distributed hydrology soil‐vegetation model (DHSVM) in a forested mountain watershed
Author(s) -
Du Enhao,
Link Timothy E.,
Gravelle John A.,
Hubbart Jason A.
Publication year - 2013
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.10110
Subject(s) - streamflow , environmental science , hydrology (agriculture) , snowpack , watershed , hydrological modelling , evapotranspiration , water content , soil science , snow , geology , drainage basin , climatology , ecology , geography , geomorphology , cartography , geotechnical engineering , machine learning , computer science , biology
Abstract Hydrologic models are often calibrated and validated with streamflow from a limited number of sites, whereas assessment of model performance with internal watershed data can be used to constrain the parameterization of physically based models to verify that specific hydrologic processes are being reasonably simulated. This is particularly important for improving the simulation accuracy of models used to evaluate potential hydrologic responses to land use and climate change. The distributed hydrology soil‐vegetation model (DHSVM) was parameterized for the Mica Creek Experimental Watershed in northern Idaho. Performance was assessed based on measured streamflow from nested and paired watersheds, snowpack dynamics, soil moisture, and transpiration estimated from sap flux. In general, DHSVM effectively simulated snowpack dynamics, soil water content, and the streamflow regime. Streamflow simulation for seven subcatchments had model efficiencies ranging between 0.63 and 0.79. Model efficiency of snowpack simulation at a SNOTEL site was 0.95. Some minor discrepancies between simulated and measured values suggested that some processes, such as snow redistribution, were not represented by the model or were insufficiently parameterized for local conditions. A sensitivity analysis indicated that soil porosity, leaf area index, and minimum stomatal resistance were among the most influential parameters that affected variations in the simulated hydrological regime. However, those variables can be reasonably estimated based on field or remote sensing data. Other important parameters, such as saturated hydraulic conductivity, are more difficult to quantify and therefore need to be refined during the calibration phase. A description of the iterative parameter refinement process that was used in the calibration phase of the model is included to assist other researchers in refining model parameterizations. Copyright © 2013 John Wiley & Sons, Ltd.